Araştırma Çıktıları

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    Systematic review and meta-analysis of within-subject and between-subject biological variation estimates of 20 haematological parameters
    (WALTER DE GRUYTER GMBH, 2020-01-01) Coskun, Abdurrahman; Braga, Federica; Carobene, Anna; Tejedor Ganduxe, Xavier; Aarsand, Aasne K.; Fernandez-Calle, Pilar; Diaz-Garzon Marco, Jorge; Bartlett, William; Jonker, Niels; Aslan, Berna; Minchinela, Joana; Boned, Beatriz; Gonzalez-Lao, Elisabet; Marques-Garcia, Fernando; Perich, Carmen; Ricos, Carmen; Simon, Margarita; Sandberg, Sverre; Chem, European Federation Clinical
    Background: Interpretation of the complete blood count (CBC) parameters requires reliable biological variation (BV) data. The aims of this study were to appraise the quality of publications reporting BV data for CBC parameters by applying the BV Data Critical Appraisal Checklist (BIVAC) and to deliver global BV estimates based on BIVAC compliant studies. Methods: Relevant publications were identified by a systematic literature search and evaluated for their compliance with the 14 BIVAC criteria, scored as A, B, C or D, indicating decreasing compliance. Global CVI and CVG estimates with 95\% CI were delivered by a meta-analysis approach using data from BIVAC compliant papers (grades A-C). Results: In total, 32 studies were identified
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    Critical appraisal and meta-analysis of biological variation estimates for kidney related analytes
    (WALTER DE GRUYTER GMBH, 2022-01-01) Jonker, Niels; Aslan, Berna; Boned, Beatriz; Marques-Garcia, Fernando; Ricos, Carmen; Alvarez, Virtudes; Bartlett, William; Braga, Federica; Carobene, Anna; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Gonzalez-Lao, Elisabet; Minchinela, Joana; Perich, Carmen; Simon, Margarita; Sandberg, Sverre; Aarsand, Aasne K.
    Objectives Kidney markers are some of the most frequently used laboratory tests in patient care, and correct clinical decision making depends upon knowledge and correct application of biological variation (BV) data. The aim of this study was to review available BV data and to provide updated BV estimates for the following kidney markers in serum and plasma
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    Critical review and meta-analysis of biological variation estimates for tumor markers
    (WALTER DE GRUYTER GMBH, 2022-01-01) Marques-Garcia, Fernando; Boned, Beatriz; Gonzalez-Lao, Elisabet; Braga, Federica; Carobene, Anna; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Carmen Perich, Maria; Simon, Margarida; Jonker, Niels; Aslan, Berna; Bartlett, William Alexander; Sandberg, Sverre; Aarsand, Aasne K.; Chem, European Federation Clinical; Database, Task Grp Biol Variation
    Objectives Biological variation data (BV) can be used for different applications, but this depends on the availability of robust and relevant BV data. In this study, we aimed to summarize and appraise BV studies for tumor markers, to examine the influence of study population characteristics and concentrations on BV estimates and to discuss the applicability of BV data for tumor markers in clinical practice. Methods Studies reporting BV data for tumor markers related to gastrointestinal, prostate, breast, ovarian, haematological, lung, and dermatological cancers were identified by a systematic literature search. Relevant studies were evaluated by the Biological Variation Data Critical Appraisal Checklist (BIVAC) and meta-analyses were performed for BIVAC compliant studies to deliver global estimates of within-subject (CVI) and between-subject (CVG) BV with 95\% CI. Results The systematic review identified 49 studies delivering results for 22 tumor markers
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    The European Biological Variation Study (EuBIVAS): a summary report
    (WALTER DE GRUYTER GMBH, 2022-01-01) Carobene, Anna; Aarsand, Aasne K.; Bartlett, William A.; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Guerra, Elena; Jonker, Niels; Locatelli, Massimo; Plebani, Mario; Sandberg, Sverre; Ceriotti, Ferruccio
    Biological variation (BV) data have many important applications in laboratory medicine. Concerns about quality of published BV data led the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) 1st Strategic Conference to indicate need for new studies to generate BV estimates of required quality. In response, the EFLM Working Group on BV delivered the multicenter European Biological Variation Study (EuBIVAS). This review summarises the EuBIVAS and its outcomes. Serum/plasma samples were taken from 91 ostensibly healthy individuals for 10 consecutive weeks at 6 European centres. Analysis was performed by Siemens ADVIA 2400 (clinical chemistry), Cobas Roche 8000, c702 and e801 (proteins and tumor markers/hormones respectively), ACL Top 750 (coagulation parameters), and IDS iSYS or DiaSorin Liaison (bone biomarkers). A strict preanalytical and analytical protocol was applied. To determine BV estimates with 95\% CI, CV-ANOVA after analysis of outliers, homogeneity and trend analysis or a Bayesian model was applied. EuBIVAS has so far delivered BV estimates for 80 different measurands. Estimates for 10 measurands (Non-HDL Cholesterol, S100-beta protein, neuron-specific enolase, soluble transferrin receptor, intact fibroblast growth-factor-23, uncarboxylated-unphosphorylated matrix-Gla protein, human epididymis protein-4, free, conjugated and \%free prostate-specific antigen), prior to EuBIVAS, have not been available. BV data for creatinine and troponin I were obtained using two analytical methods in each case. The EuBIVAS has delivered high-quality BV data for a wide range of measurands. The BV estimates are for many measurands lower than those previously reported, having an impact on the derived analytical performance specifications and reference change values.
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    Within- and between-subject biological variation data for tumor markers based on the European Biological Variation Study
    (WALTER DE GRUYTER GMBH, 2022-01-01) Coskun, Abdurrahman; Aarsand, Aasne K.; Sandberg, Sverre; Guerra, Elena; Locatelli, Massimo; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Ceriotti, Ferruccio; Jonker, Niels; Bartlett, William A.; Carobene, Anna; Chem, European Federation Clinical
    Objectives: Reliable biological variation (BV) data are required for the clinical use of tumor markers in the diagnosis and monitoring of treatment effects in cancer. The European Biological Variation Study (EuBIVAS) was established by the EFLM Biological Variation Working Group to deliver BV data for clinically important measurands. In this study, EuBIVAS-based BV estimates are provided for cancer antigen (CA) 125, CA 15-3, CA 19-9, carcinoembryonic antigen, cytokeratin-19 fragment, alpha-fetoprotein and human epididymis protein 4. Methods: Subjects from five European countries were enrolled in the study, and weekly samples were collected from 91 healthy individuals (53 females and 38 males
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    Biological variation estimates of thyroid related measurands - meta-analysis of BIVAC compliant studies
    (WALTER DE GRUYTER GMBH, 2022-01-01) Fernandez-Calle, Pilar; Diaz-Garzon, Jorge; Bartlett, William; Sandberg, Sverre; Braga, Federica; Beatriz, Boned; Carobene, Anna; Coskun, Abdurrahman; Gonzalez-Lao, Elisabet; Marques, Fernando; Perich, Carmen; Simon, Margarida; Aarsand, Aasne K.; Variation, E.F.L.M. Working Grp Biol; Database, Task Grp Biol Variation
    Objectives Testing for thyroid disease constitutes a high proportion of the workloads of clinical laboratories worldwide. The setting of analytical performance specifications (APS) for testing methods and aiding clinical interpretation of test results requires biological variation (BV) data. A critical review of published BV studies of thyroid disease related measurands has therefore been undertaken and meta-analysis applied to deliver robust BV estimates. Methods A systematic literature search was conducted for BV studies of thyroid related analytes. BV data from studies compliant with the Biological Variation Data Critical Appraisal Checklist (BIVAC) were subjected to meta-analysis. Global estimates of within subject variation (CVI) enabled determination of APS (imprecision and bias), indices of individuality, and indicative estimates of reference change values. Results The systematic review identified 17 relevant BV studies. Only one study (EuBIVAS) achieved a BIVAC grade of A. Methodological and statistical issues were the reason for B and C scores. The meta-analysis derived CVI generally delivered lower APS for imprecision than the mean CVA of the studies included in this systematic review. Conclusions Systematic review and meta-analysis of studies of BV of thyroid disease biomarkers have enabled delivery of well characterized estimates of BV for some, but not all measurands. The newly derived APS for imprecision for both free thyroxine and triiodothyronine may be considered challenging. The high degree of individuality identified for thyroid related measurands reinforces the importance of RCVs. Generation of BV data applicable to multiple scenarios may require definition using ``big data{''} instead of the demanding experimental approach.
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    European Biological Variation Study (EuBIVAS): within- and between-subject biological variation estimates for serum thyroid biomarkers based on weekly samplings from 91 healthy participants
    (WALTER DE GRUYTER GMBH, 2022-01-01) Bottani, Michela; Aarsand, Aasne K.; Banfi, Giuseppe; Locatelli, Massimo; Coskun, Abdurrahman; Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Sandberg, Sverre; Ceriotti, Ferruccio; Carobene, Anna; Chem, European Federation Clinical
    Objectives Thyroid biomarkers are fundamental for the diagnosis of thyroid disorders and for the monitoring and treatment of patients with these diseases. The knowledge of biological variation (BV) is important to define analytical performance specifications (APS) and reference change values (RCV). The aim of this study was to deliver BV estimates for thyroid stimulating hormone (TSH), free thyroxine (FT4), free triiodothyronine (FT3), thyroglobulin (TG), and calcitonin (CT). Methods Analyses were performed on serum samples obtained from the European Biological Variation Study population (91 healthy individuals from six European laboratories
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    Within-subject and between-subject biological variation estimates of 21 hematological parameters in 30 healthy subjects
    (WALTER DE GRUYTER GMBH, 2018-01-01) Coskun, Abdurrahman; Carobene, Anna; Kilercik, Meltem; Serteser, Mustafa; Sandberg, Sverre; Aarsand, Aasne K.; Fernandez-Calle, Pilar; Jonker, Niels; Bartlett, William A.; Diaz-Garzon, Jorge; Huet, Sibel; Kiziltas, Cansu; Dalgakiran, Ilayda; Ugur, Esra; Unsal, Ibrahim; Varia, E.F.L.M. Working Grp Biological
    Background: The complete blood count (CBC) is used to evaluate health status in the contexts of various clinical situations such as anemia, infection, inflammation, trauma, malignancies, etc. To ensure safe clinical application of the CBC, reliable biological variation (BV) data are required. The study aim was to define the BVs of CBC parameters employing a strict protocol. Methods: Blood samples, drawn from 30 healthy subjects (17 females, 13 males) once weekly for 10 weeks, were analyzed using a Sysmex XN 3000 instrument. The data were assessed for normality, trends, outliers and variance homogeneity prior to coefficient of variation (CV)-analysis of variance (ANOVA). Sex-stratified within-subject (CVI) and between-subjects (CVG) BV estimates were determined for 21 CBC parameters. Results: For leukocyte parameters, with the exception of lymphocytes and basophils, significant differences were found between female/male CVI estimates. The mean values of all erythrocyte-, reticulocyte- and platelet parameters differed significantly between the sexes, except for mean corpuscular hemoglobin concentration, mean corpuscular volume and platelet numbers. Most CVI and CVG estimates appear to be lower than those previously published. Conclusions: Our study, based on a rigorous protocol, provides updated and more stringent BV estimates for CBC parameters. Sex stratification of data is necessary when exploring the significance of changes in consecutive results and when setting analytical performance specifications.
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    Long-term within- and between-subject biological variation of 29 routine laboratory measurands in athletes
    (WALTER DE GRUYTER GMBH, 2022-01-01) Diaz-Garzon, Jorge; Fernandez-Calle, Pilar; Aarsand, Aasne K.; Sandberg, Sverre; Coskun, Abdurrahaman; Carobene, Anna; Jonker, Niels; Itkonen, Outi; Bartlett, William A.; Buno, Antonio; Chem, European Federation Clinical
    Objectives Within- and between-subject biological variation (BV) estimates have many applications in laboratory medicine. However, robust high-quality BV estimates are lacking for many populations, such as athletes. This study aimed to deliver BV estimates of 29 routine laboratory measurands derived from a Biological Variation Data Critical Appraisal Checklist compliant design in a population of high-endurance athletes. Methods Eleven samples per subject were drawn from 30 triathletes monthly, during a whole sport season. Serum samples were measured in duplicate for proteins, liver enzymes, lipids and kidney-related measurands on an Advia2400 (Siemens Healthineers). After outlier and homogeneity analysis, within-subject (CVI) and between-subject (CVG) biological variation estimates were delivered (CV-ANOVA and log-ANOVA, respectively) and a linear mixed model was applied to analyze the effect of exercise and health related variables. Results Most CVI estimates were similar or only slightly higher in athletes compared to those reported for the general population, whereas two- to three-fold increases were observed for amylase, ALT, AST and ALP. No effect of exercise and health related variables were observed on the CVI estimates. For seven measurands, data were not homogeneously distributed and BV estimates were therefore not reported. Conclusions The observation of higher CVI estimates in athletes than what has been reported for the general population may be related to physiological stress over time caused by the continuous practice of exercise. The BV estimates derived from this study could be applied to athlete populations from disciplines in which they exercise under similar conditions of intensity and duration.
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    The European Biological Variation Study (EuBIVAS): Biological Variation Data for Coagulation Markers Estimated by a Bayesian Model
    (OXFORD UNIV PRESS INC, 2021-01-01) Aarsand, Aasne K.; Kristoffersen, Ann Helen; Sandberg, Sverre; Stove, Bard; Coskun, Abdurrahman; Fernandez-Calle, Pilar; Diaz-Garzon, Jorge; Guerra, Elena; Ceriotti, Ferruccio; Jonker, Niels; Roraas, Thomas; Carobene, Anna; Chem, European Federation Clinical
    BACKGROUND: For biological variation (BV) data to be safely used, data must be reliable and relevant to the population in which they are applied. We used samples from the European Biological Variation Study (EuBIVAS) to determine BV of coagulation markers by a Bayesian model robust to extreme observations and used the derived within-participant BV estimates {[}CVP(i)] to assess the applicability of the BV estimates in clinical practice. METHOD: Plasma samples were drawn from 92 healthy individuals for 10 consecutive weeks at 6 European laboratories and analyzed in duplicate for activated partial thromboplastin time (APTT), prothrombin time (PT), fibrinogen, D-dimer, antithrombin (AT), protein C, protein S free, and factor VIII (FVIII). A Bayesian model with Student t likelihoods for samples and replicates was applied to derive CVP(i) and predicted BV estimates with 95\% credibility intervals. RESULTS: For all markers except D-dimer, CVP( i) were homogeneously distributed in the overall study population or in subgroups. Mean within-subject estimates (CVI) were <5\% for APTT, PT, AT, and protein S free, <10\% for protein C and FVIII, and <12\% for fibrinogen. For APTT, protein C, and protein S free, estimates were significantly lower in men than in women <= 50 years. CONCLUSION: For most coagulation markers, a common CVI estimate for men and women is applicable, whereas for APTT, protein C, and protein S free, sex-specific reference change values should be applied. The use of a Bayesian model to deliver individual CVP(i) allows for improved interpretation and application of the data.